calibration and evaluation of three cropgro models under different water regimes in a semi-arid...
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Calibration and Evaluation of Three CROPGRO Models under Different Water Regimes in a
Semi-Arid Tropical Environment
Kindie TesfayeHaramaya University, Ethiopia
16 Dec 2008
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Outline of presentation
Introduction Ethiopia Subject
Methodology Results Conclusion
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Introduction
The topic presented is result of research conducted in Ethiopia
Ethiopia is one of the ancient civilized countries
Has its own calendar (Julian) and Alphabets Federal administration (14 states)
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Country profile Location: 8o 00 N, 38o 00 E Area: 1.13 million sq km (437,794 sq miles) Elevation: -125 to 4620 m Population: 75 million (UN, 2007) Capital: Addis Ababa Major languages: Amharic, Oromo, Tigrinya, Somali, English
(schools) Major religions: Christianity, Islam Main exports: Coffee, hides, cereals, oilseeds, grain legumes,
beeswax, sugar, cotton, cut flowers, livestock products Natural recourses: reserves of gold, platinum, copper, potash,
natural gas, petroleum, hydropower Tourist attractions: National game reserves (parks), historical
places, the oldest human fossils found (e.g. Lucy-3.18 m yrs old).
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Endemic Animals and Plants
Chilada Baboon Walia Ibex23 endemic birds
Red fox
Mountain Nyala Colobus Monkey Oryx Spps.
Many plant genetic resources
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Country profile-historical places
Axum Stelle- > 2000 yrs old
Blue Nile Water Falls
Sofamar Natural cave
Axum Zion- the oldest church Fasilede Palace –built in 16th C
Lalibela rock hewn churches-built in the 12th C.
Negash Mosque- 2000 yrs old
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Challenges
Climate variability Recurrent drought Crop failures Deforestation Soil Degradation
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Challenges… Almost half of the country is in the semi-arid climate belt Agricultural decision making is difficult
Climate variability Climate change Poor research and extension coverage lack of interdisciplinary approach
Grain legumes (drybean, chickpea, cowpea) are relegated to marginal areas
the majority of the production of these crops comes from the semi-arid parts of the country
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Crop models could play an important role in managing agricultural production in the these areas because:
Involve integrated approach (climate, soil, crop, management) at once
fast results
Inexpensive
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The CSM-CROPGRO model has been used to study and evaluate several production problems including:
climate change (e.g. Mera et al., 2006; Challinor and Wheeler, 2008)
spatial yield variability (Paz et al., 2001)
water related constraints (e.g. Ruiz-Noueira et al., 2001)
plating date and cultivar selection ( Cooper et al., 2006)
plant population and fertilizer interactions (Meirles et al., 2002)
optimum irrigation optimization (Faria et al., 1997; Heinemann et al., 2000).
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Objective
To calibrate and evaluate CROPGRO-drybean, chickpea and cowpea under three water regimes in a semi-arid tropical environment
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Methodology
Site: Dire Dawa latitude 9o6’N longitude 41o8’ E altitude 1197 m
Season: Three seaosns Dec, 2001-March, 2002 April-July, 2002 Oct, 2002-March, 2003
Treatments: Three water regimes Well-irrigated control (C) Mid-season water deficit (MS) Late-season water deficit (LS) Three crops (drybean, chickpea, cowpea)
Design: Split-plot in RCBD (WR: main plot; Water regimes: main-plot; Crops: sub-plot
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Data collection Phenology Growth, Yield & YC Soil water Physiology (PS, SC, LWP) Canopy and soil temp. Radiation interception Weather Soil (initial, profile) Crop management
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Methodology… Data organization for DSSAT format
data were organized and all the required files created (Soil.Soil, WTH files, Xfiles, A files, T files)
Calibration the 2001/2003 well-irrigated treatment of the respective spps. Stepwise calibration followed
First phenological parameters using Gencalc Growth and yield: sensitivity analysis using the data in the Tfiles
Evaluation Comparing simulated and measured phenology, growth and yield
parameters with using RMSE MAD CV (%) Willmot’s Index of agreement (d) Coefficient of determination (R2)
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Results-Calibration
Genetic coefficients Drybean Chickpea Cowpea Critical short day length (h) 12.17 9.90 10.82 Slope of relative response to photoperiod (h-1) 0.00 -0.143 0.020 Time from emergence to flower appearance (pda) 33.10 33.00 32.40 Time from first flower to first pod (pda) 2.00 8.00 2.50 Time from first flower to first seed (pda) 8.21 8.64 4.25 Time from first seed to physiological maturity (pda) 26.40 46.00 27.60 Time from first flower and end of leaf expansion (pda) 15.10 32.21 16.50 Maximum leaf photosynthesis (mg CO2 m
-2 s-1) 1.44 1.19 1.19 Specific leaf area (cm2g-1) 183.00 138.10 150.00 Maximum leaf size (cm2) 133.00 10.00 240.00 Maximum fraction of partitioning to seeds and shell 0.90 0.60 0.95 Maximum weight per seed (g) 0.276 0.352 0.171 Seed filling duration (pda) 9.75 17.90 16.74 Seeds per pod (no. pod-1) 7.30 2.00 11.05 Pod addition duration (pda) 9.40 11.00 14.60 Shelling percentage 78.00 85.00 77.70 Fraction protein in seeds (g g-1) 0.235 0.216 0.300 Fraction oil in seeds (g g-1) 0.030 0.048 0.065
Table 1. Calibrated genetic coefficients of drybean, chickpea, cowpea using data from a well-irrigated experiment
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Result-Calibration…
RMSE = 0.59; d = 0.95
0.0
1.0
2.0
3.0
4.0
5.0
6.0
0 20 40 60 80 100 120
LA
I
SimulatedMeasured
Drybean
RMSE = 0.26; d = 0.99
0.0
1.0
2.0
3.0
4.0
5.0
6.0
0 20 40 60 80 100 120
Days after planting
LA
I
Cowpea
RMSE = 0.35; d = 0.97
0.0
1.0
2.0
3.0
4.0
5.0
6.0
0 20 40 60 80 100 120
Days after planting
LA
I
Chickpea
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Results-Calibration…
BM (RMSE = 1083; d = 0.99)PW (RMSE = 405; d = 0.99)
0
4000
8000
12000
16000
0 20 40 60 80 100 120
Dry
w
eig
t (
kg h
a-1
)
Simulated-BMMeasured-BMSimulated-PWmeasured-PW
Drybean
BM (RMSE = 513; d = 0.99)PW (RMSE = 341; d = 0.99)
0
4000
8000
12000
16000
0 20 40 60 80 100 120
Days after planting
Dry
wei
gt
(kg
ha
-1)
Cowpea
BM (RMSE = 375; d = 0.99)PW (RMSE = 391; d = 0.95)
0
4000
8000
12000
16000
0 20 40 60 80 100 120
Days after planting
Chickpea
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Results-Calibration…
Parameter Drybean Chickpea Cowpea
S M S M S M
DTF (dap) 42 42 53 53 45 45
DTFP (dap) 51 NA 57 NA 47 48
DTFS (dap) 51 51 59 57 63 NA
DTPM (dap) 104 105 104 104 99 100
GY (kg/ha) 1767 1765 2553 2537 4177 4122
SN (m-2) 593 591 1191 NA 1820 1809
SW (g/unit) 0.30 0.30 0.21 0.23 0.23 0.24
SN per pod 2.01 2.00 11.10 11.00 7.40 7.40
ABM (kg/ha) 6296 6406 6230 6264 11240 11457
LAImax 2.94 2.98 3.65 3.65 4.1 4.1
HI 0.28 0.28 0.41 0.41 0.37 0.36
Shell perc. 86.1 86.0 78.7 NA 78.5 79.3
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Results-Model Evaluation1. Soil water
Chickpea-MS
0.00
0.10
0.20
0.30
0.40
0.50
0 20 40 60 80
Days after planting
So
il w
ater
(cm
3 cm
-3)
DUL
DLLRMSE = 0.025; d = 0.93
Chickpea-LS
0.00
0.10
0.20
0.30
0.40
0.50
0 20 40 60 80 100
Days after planting
RMSE = 0.023; d = 0.94
Beans-MS
0.00
0.10
0.20
0.30
0.40
0.50
0 20 40 60 80 100
So
il w
ater
(cm
3 cm
-3)
MeasuredSimulated
DUL
DLL
RMSE = 0.029; d = 0.89
Beans-LS
0.00
0.10
0.20
0.30
0.40
0.50
0 20 40 60 80 100
RMSE = 0.034; d = 0.85
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Results-Model Evaluation…
Cowpea-MS
0.00
0.10
0.20
0.30
0.40
0.50
0 20 40 60 80 100
Days after planting
So
il w
ater
(cm
3 cm
-3)
DUL
DLL
RMSE = 0.026; d = 0.92
Cowpea-LS
0.00
0.10
0.20
0.30
0.40
0.50
0 20 40 60 80 100
Days after planting
RMSE = 0.031; d = 0.90
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Results-Model Evaluation…
Mean Evaluation statistics
S M MAD RMSE CV(%) d
Drybean 45.0 45.9 0.88 1.5 3.2 0.95
Chickpea 40.6 41.6 1.0 1.3 3.2 0.69
Cowpea 49.3 50.4 1.9 1.9 3.8 0.98
2. Days to flowering (dap)
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Results-Model Evaluation…
Species WR Mean Comparison statistics
S M MAD RMSE CV (%) d
Drybean C 95 93 2.0 2.8 3.1 0.91
MS 94 91 7.0 7.1 7.8 0.75
LS 89 79 10.3 10.4 13.2 0.58
Pooled 92 87 7.0 7.8 9.0 0.77
Chickpea C 98 94 3.5 4.3 4.6 0.73
MS 87 78 9 11.7 14.9 0.66
LS 89 79 10.3 10.4 13.2 0.58
Pooled 90 82 8.0 10.0 12.1 0.71
Cowpea C 99 96 4.0 4.0 4.2 0.77
MS 95 88 7.7 7.9 9.0 0.68
LS 94 83 11.0 11.1 13.4 0.51
Pooled 96 88 8.0 8.6 9.8 0.66
3. Physiological maturity
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Results-Model Evaluation…4. Growth-drybean
C (RMSE = 0.75; d = 0.92) MS (RMSE = 1.0; d = 0.83) LS (RMSE = 1.2; d = 0.85)
0.0
1.0
2.0
3.0
4.0
5.0
0 20 40 60 80 100 120
Days after planting
LA
I
Simulated-MS Measured-MSSimulated-LS Measured-LSSimulated-C Measured-C
LAI
C (RMSE = 1697; d = 0.96)MS (RMSE = 1113; d = 0.92)LS (RMSE = 1429; d = 0.95)
0
2000
4000
6000
8000
10000
12000
20 40 60 80 100 120
Bio
mas
s (k
g h
a-1)
Biomass
C (RMSE = 757; d = 0.93)MS (RMSE = 459; d = 0.82)LS (RMSE = 763; d = 0.87)
0
1000
2000
3000
4000
5000
6000
20 40 60 80 100 120Days after planting
Po
d w
eig
ht
(kg
ha
-1)
Pod growth
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Results-Model Evaluation…4. Growth-chickpea
C (RMSE = 848; d = 0.99)MS (RMSE = 484; d = 0.99)LS (RMSE = 706; d = 0.98)
0
2000
4000
6000
8000
10000
12000
20 40 60 80 100 120
Bio
mas
s (k
g h
a-1)
Biomass
C (RMSE = 775; d = 0.94)MS (RMSE = 373; d = 0.93)LS (RMSE = 441; d = 0.90
0
1000
2000
3000
4000
5000
6000
20 40 60 80 100 120
Days after emergence
Po
d w
eig
ht
(kg
ha
-1)
Pod growth
C (RMSE = 0.28; d = 0.99)MS (RMSE = 0.91; d =0.78)LS (RMSE = 0.63; d = 0.94)0.0
1.0
2.0
3.0
4.0
20 40 60 80 100 120
Days after planting
LA
I
Simulated-C Simulated-MSSimulated-LS Measured-CMeasured-MS Measured-LS
LAI
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Results-Model Evaluation…4. Growth-cowpea
C (RMSE = 0.60; d = 0.95)MS (RMSE = 0.57; d = 0.65)LS (RMSE = 0.98; d = 0.91)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
20 40 60 80 100 120Days after planting
LA
I
LAIC (RMSE = 1343; d = 0.96)MS (RMSE = 1178; d = 0.98)LS (RMSE = 1306; d = 0.93)
0
2000
4000
6000
8000
10000
12000
20 40 60 80 100 120
Bio
mas
s (k
g h
a-1)
Biomass
C (RMSE = 542; d = 0.97)MS (RMSE = 847; d = 0.82)LS (RMSE = 458; d = 0.92)
0
1000
2000
3000
4000
5000
6000
20 40 60 80 100 120
Days after planting
Po
d
wei
gh
t (k
g h
a-1)
Simulated-CMeasured-CSimulated-MSMeasured-MSSimulated-LSMeasured-LS
Pod growth
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Results-Model Evaluation…4. Grain yield (kg ha-1)
RMSE = 441 MAD = 367
CV = 23% d = 0.95
R2 = 0.940
1000
2000
3000
4000
0 1000 2000 3000 4000
Simulated
Mea
sure
d
CMSLS
Drybean 1:1 line
RMSE = 248 MAD = 207
CV = 23% d = 0.95
R2 = 0.940
1000
2000
3000
4000
0 1000 2000 3000 4000
Simulated
Mea
sure
d
Chickpea
RMSE = 292 MAD = 254 CV = 27% d = 0.87
R2 = 0.90
0
1000
2000
3000
4000
0 1000 2000 3000 4000
Simluated
Mea
sure
d
Cowpea
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Results-Model Evaluation…
5. Relative yield reduction
0.00
0.20
0.40
0.60
0.80
MS LS C
Water regimes
Mea
n r
elat
ive
yiel
d r
edu
ctio
n
Measured
Simulated
Chickpea
0.00
0.20
0.40
0.60
0.80
1.00
MS LS C
Water regimes
Mea
n r
elat
rive
yie
ld r
edu
ctio
n
Measured
Simulated
Drybean
0.00
0.20
0.40
0.60
0.80
1.00
MS LS C
Water regimes
Mea
n r
elat
ive
yiel
d r
edu
ctio
n
Measured
Simulated
Cowpea
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Results-Model Evaluation…5. Simulated WSF vs. Measured LWP
y = -0.84x - 0.85; R2 = 0.60
0.00
0.20
0.40
0.60
0.80
1.00
-4.0 -3.0 -2.0 -1.0 0.0
Measured leaf water potential (MPa)
Sim
ula
ted
wat
er s
tres
s fa
cto
r
Cowpea
y = -0.57x - 1.10, R2 = 0.88
0.00
0.20
0.40
0.60
0.80
1.00
-4.0 -3.0 -2.0 -1.0 0.0
Measured Leaf water potential (MPa)
Sim
ula
ted
wat
er s
tres
s fa
cto
r ChickpeaDryean
y = -1.71x - 2.19, R2 = 0.80
0.00
0.20
0.40
0.60
0.80
1.00
-4.0 -3.0 -2.0 -1.0 0.0
So
il w
ater
str
ess
fact
or 2002
2002/03
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Conclusion The CSM-CROPGRO- drybean, chickpea and cowpea models
accurately simulated:
soil water dynamics in the root zone layer and the duration and intensity of water deficit occurrence during the growing seasons
the seasonal pattern of LAI, biomass accumulation and pod growth under different water regimes although accuracy is less in the MS treatment, and
grain yield variability with water supply.
The models overestimated the duration of physiological maturity under water deficit conditions suggesting the need for further improvement in this regard.
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Conclusion…
If properly calibrated, the models have shown their ability to be used as decision support tools in:
irrigation water management, choice of cultivars to different water supply
environments, prescreening of genotypes for drought tolerance and determining the occurrence and severity of agricultural
drought in the semi-arid tropical environments.
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